SRE is a technique for achieving high-resolution quality text and graphics. In SRE applications, high-resolution patterns are encoded as gray pixel values at lower resolution and then decoded on the IOT (Image Output Terminal) sometimes also referred to as a print engine module. In this case, the pixel tag (e.g., rendering hints) directs the IOT to decode the intensity plane while considering the same as an encoded pattern. The basic concept of SRE was developed to realize higher-resolution patterns even from lower resolution buffer data.
SRE can function as a filter and offers better filtering capabilities than, for example, anti-aliasing filters, to address the “jagging” problem along the edges of an object, particularly for tiny or down-sampled text and graphics. This approach uses the IOT capability of printing in, for example, 2400 DPI. For the classical SRE used in FFPS, the edge patterns along the 4 sub-pixels in intermediate 1200 DPI raster (which are actually in combination representing 1 pixel in 600 DPI) are encoded. The intensity array of color separation (e.g., K 100%) is replaced with encoded pattern value and the corresponding tag holds a unique value to declare that pixel as an SRE pattern rather than a value of intensity.
The IOT, at the end, can decode the pattern and print accurate pattern in 1200 DPI even from 600 DPI data. In 1200 DPI, i.e., 4 sub-pixels from 1 pixel of 600 DPI, we can have total 24=16 patterns. The intensity array for each of the color separation of each of the pixel is represented by 1 byte, i.e., 8 bits. Therefore 28=256 patterns can be realized, at the most. In 1200 DPI, for example, the number of patterns (16) is well fitted into the available patterns (256).
In order to achieve even better edge accuracy and utilize the IOT even more effectively, it would be desirable to achieve 2400 DPI pattern. However, each pixel in 600 DPI forms 16 sub-pixels in 2400 DPI. Hence, this results in 216=65536 number of patterns or distinct encoded values. This new number (216=65536) is significantly higher than the allowed number of encoded patterns (216=65536) to be represented in 600 DPI intensity array.
The present inventors believe that a solution as discussed in greater detail herein involves the implementation of an adaptive approach for optimizing, for example, the most suitable or likely patterns from the available 65536 patterns to fit into an allowed number of encoded values (e.g., 256 for 8 bit quantization and 1024 for 10 bit quantization).